Many of the emerging technologies that will be entering the market in 2033 are already known in some form in 2008, according to Gartner.
Many of the innovations that will unfold during the next 25 years can be found today in research papers, patents, or are in a prototype in production.
These long-term innovations, taking place in 5-20 years, go beyond the range of the typical IT project portfolio planning cycle. These innovations are classified as 'IT grand challenges'. Gartner defines an IT grand challenge as a fundamental issue to be overcome within the field of IT whose resolutions will have broad and extremely beneficial economic, scientific or societal effects on all aspects of our lives.
"IT leaders should always be looking ahead for the emerging technologies that will have a dramatic impact on their business, and information on many of these future innovations are already in some public domain," said Ken McGee, vice president and Gartner Fellow. "Today, CIOs should identify which Gartner IT grand challenges will be most meaningful for their organisations. Then within the next 12 months, review patents for additional IT grand challenge candidates.
Gartner has identified seven IT grand challenges. They include:
* Never having to manually recharge devices: today, the ubiquity of portable computing and communications devices powered by battery means that many people would find it highly desirable to either have their batteries charged remotely or their devices powered by a remote source, bypassing the use of batteries altogether. Despite more than 100 years of research since the invention of the Tesla Coil in the late nineteenth century, the most notable progress to date was achieved by the Massachusetts Institute of Technology (MIT) in July 2007 in their experiment to transfer non-radiative power. By this measure, any commercial application of wireless powering still seems a long way off.
* Parallel programming: rather than simply creating faster single-core processors to perform tasks serially, another way to meet the constant demand for faster processor speed is to develop multiple, slower speed processors that perform tasks serially. Simulations, modelling, entertainment and massive data mining would all benefit from advances in parallel computing. However, a challenge with parallel computing is to create applications that fully exploit a 'multicore' architecture by dividing a problem into smaller individual problems addressed by individual processors. To overcome this, key issues will need to be addressed, including effectively breaking up processes into specific sub-processes, determining which tasks can be handled simultaneously by multiple processes, scheduling tasks to be processed simultaneously and designing the architecture of the parallel processing environment.
* Non tactile, natural computing interface: The idea of interacting with computers without any mechanical interface has long been a desirable goal in computing. Some of the many challenges that remain in this area include the ability to detect gestures, developing a gesture dictionary and the need for realtime processing. Another set of challenges relate to natural language processing, which include speech synthesis, speech recognition, natural language understanding, natural language generation, machine translation and translating one natural language into another.
* Automated speech translation: once the many hurdles of natural language processing are overcome to yield human-to-computer communications in one language, the complexity extends further when translation and output is required to a target language that is understandable to a human. Some rudimentary systems have already been created to accomplish basic speech translation, such as one-way and two-way translations.
* Persistent and reliable long-term storage: current technologies are hard-pressed to perfectly preserve Dr. Francine Berman's 2006 estimate of 161 Exabytes (x10 to the 18th power) of digital information on digital media for more than 20 years. The barriers to long-term archiving (in excess of 100 years) that must be overcome include format, hardware, software, metadata, information retrieval, just to mention a few.
* Increase programmer productivity 100-fold: as business and society's demand for software development increases, and the apparent decline of students pursuing software engineering and computer science degrees intensifies, removing uncertainty from meeting future demands will have to be met by increasing the output, or productivity, per programmer. While the exploration and development of tools to enhance productivity continues to capture attention, it would appear that effectively and efficiently exploiting re-usable code is one of the most encouraging rays of hope to yield more output per programmer. But many challenges exist there as well. Minimising the time required to find the perfect software module and avoiding the need to modify re-usable software are among the many challenges.
* Identifying the financial consequences of IT investing: one of the most perplexing challenges faced by IT leaders has been to convey the business value of IT in terms readily understandable by business executives. As a discipline that conveys the business performance and results to internal executives and personnel only, management accounting could offer business advice and recommendations that would quantify the consequences of a particular IT deployment.
Unlike financial accounting measurements which are standard across public companies, the particular management accounting metrics could be different for each company. This grand challenge would be considered conquered when a request for an IT project was argued with the following certainty: "If you invest in our IT proposal, you will see an additional $0,03 earnings per share directly attributable to this project by the third quarter of next year."